Magnetoencephalography for brain electrophysiology and imaging

Synergistic association of Aβ and tau pathology with cortical neurophysiology and cognitive decline in asymptomatic older adults

Animal and computational models of Alzheimer's disease (AD) indicate that early amyloid-β (Aβ) deposits drive neurons into a hyperactive regime, and that subsequent tau depositions manifest an opposite, suppressive effect as behavioral deficits emerge. Here we report analogous changes in macroscopic oscillatory neurophysiology in the human brain. We used positron emission tomography and task-free magnetoencephalography to test the effects of Aβ and tau deposition on cortical neurophysiology in 104 cognitively unimpaired older adults with a family history of sporadic AD. In these asymptomatic individuals, we found that Aβ depositions colocalize with accelerated neurophysiological activity. In those also presenting medial-temporal tau pathology, linear mixed effects of Aβ and tau depositions indicate a shift toward slower neurophysiological activity, which was also linked to cognitive decline. We conclude that early Aβ and tau depositions relate synergistically to human cortical neurophysiology and subsequent cognitive decline. Our findings provide insight into the multifaceted neurophysiological mechanisms engaged in the preclinical phases of AD.

Reduced Cortical Excitability is Associated with Cognitive Symptoms in Concussed Adolescent Football Players

BACKGROUND

American tackle football is associated with high rates of concussion, leading to neurophysiological disturbances and debilitating clinical symptoms. Previous investigations of the neurophysiological effects of concussion have largely ignored aperiodic neurophysiological activity, which is a marker of cortical excitability.

PURPOSE

We examined whether concussion during a season of high school football is related to changes in aperiodic and periodic neurophysiological activity and whether any such changes are associated with clinical outcomes.

MATERIALS AND METHODS

Pre- and post-season resting-state magnetoencephalography (MEG) data were collected from 91 high school football players over as many as four seasons of play, for a total of 278 data collections. During these seasons of football play, a cohort of 10 individuals were diagnosed with concussion. MEG data were source-imaged, frequency-transformed and parameterized, and linear mixed models were used to examine effects of concussion on pre-to-post-season changes in neurophysiological activity. Scores on the Post-Concussive Symptom Inventory were correlated with pre-to-post-season neurophysiological changes to determine their clinical relevance.

RESULTS

Concussion was associated with increased aperiodic exponents in superior frontal cortices, indicating a relative reduction in cortical excitability. This slowing of aperiodic neurophysiology mediated concussion effects on raw delta and gamma power and was associated with worse cognitive concerns across participants. Pre-to-post-season changes in aperiodic-corrected alpha and theta rhythmic activity were also decreased in posterior cortices in concussed players.

CONCLUSION

These findings indicate that concussion alters both the excitability and rhythmic signaling of the cortex, with differing spatial topographies and implications for clinical symptoms.

Combination of magnetoencephalographic and clinical features to identify atypical self-limited epilepsy with centrotemporal spikes

INTRODUCTION

Our aim was to use magnetoencephalography (MEG) and clinical features to early identify self-limited epilepsy with centrotemporal spikes (SeLECTS) patients who evolve into atypical SeLECTS (AS).

METHODS

The baseline clinical and MEG data of 28 AS and 33 typical SeLECTS (TS) patients were collected. Based on the triple-network model, MEG analysis included power spectral density representing spectral power and corrected amplitude envelope correlation representing functional connectivity (FC). Based on the clinical and MEG features of AS patients, the linear support vector machine (SVM) classifier was used to construct the prediction model.

RESULTS

The spectral power transferred from the alpha band to the delta band in the bilateral posterior cingulate cortex, and the inactivation of the beta band in both the right anterior cingulate cortex and left middle frontal gyrus were distinctive features of the AS group. The FC network in the AS group was characterized by attenuated intrinsic FC within the salience network in the alpha band, as well as attenuated FC interactions between the salience network and both the default mode network and central executive network in the beta band. The prediction model that integrated MEG and clinical features had a high prediction efficiency, with an accuracy of 0.80 and an AUC of 0.84.

CONCLUSION

The triple-network model of early AS patients has band-dependent MEG alterations. These MEG features combined with clinical features can efficiently predict AS at an early stage.

Magnetic Detection of Neural Activity by Nanocoil Transducers

Electrophysiological recordings from brain cells are performed routinely using implanted electrodes, but they traditionally require a wired connection to the outside of the brain. A completely passive, wireless device that does not require on-board power for active transmission but that still facilitates remote detection could open the door for mass-scale direct recording of action potentials and transform the way we acquire brain signals. We present a nanofabricated coil that forms a neuroelectromagnetic junction, yielding a highly enhanced magnetic field transduction of electrophysiology. We show that this micrometer-scale device enables remote magnetic detection of neuronal fields from the center of the coil using room temperature superconducting quantum interference device (SQUID) microscopy. Further, time-locked stimulation in conjunction with magnetometry demonstrates thresholding behavior that affirms the viability of the technology for detection with no requirement for wires or on-board power. This strategy may permit unprecedented detection of electrophysiology using magnetoencephalography and magnetic resonance imaging.

Integrating brainstem and cortical functional architectures

The brainstem is a fundamental component of the central nervous system, yet it is typically excluded from in vivo human brain mapping efforts, precluding a complete understanding of how the brainstem influences cortical function. In this study, we used high-resolution 7-Tesla functional magnetic resonance imaging to derive a functional connectome encompassing cortex and 58 brainstem nuclei spanning the midbrain, pons and medulla. We identified a compact set of integrative hubs in the brainstem with widespread connectivity with cerebral cortex. Patterns of connectivity between brainstem and cerebral cortex manifest as neurophysiological oscillatory rhythms, patterns of cognitive functional specialization and the unimodal-transmodal functional hierarchy. This persistent alignment between cortical functional topographies and brainstem nuclei is shaped by the spatial arrangement of multiple neurotransmitter receptors and transporters. We replicated all findings using 3-Tesla data from the same participants. Collectively, this work demonstrates that multiple organizational features of cortical activity can be traced back to the brainstem.

Application of magnetoencephalography in epilepsy

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that can detect whole-brain neuroelectromagnetic signals in real-time in a single measurement. Due to excellent temporal and spatial resolution and integration of computed tomography or magnetic resonance imaging data, MEG allows signal source analysis. It can pinpoint epileptic foci as well as functional brain regions, reducing the necessity for invasive electrode implantation.

Adolescent alcohol consumption predicted by differences in electrophysiological functional connectivity and neuroanatomy

Alcohol consumption during adolescence has been associated with neuroanatomical abnormalities and the appearance of future disorders. However, the latest advances in this field point to the existence of risk profiles which may lead to some individuals into an early consumption. To date, some studies have established predictive models of consumption based on sociodemographic, behavioral, and anatomical-functional variables using MRI. However, the neuroimaging variables employed are usually restricted to local and hemodynamic phenomena. Given the potential of connectome approaches, and the high temporal dynamics of electrophysiology, we decided to explore the relationship between future alcohol consumption and electrophysiological connectivity measured by MEG in a cohort of 83 individuals aged 14 to 16. As a result, we found a positive correlation between alcohol consumption and the functional connectivity in frontal, parietal, and frontoparietal connections. Once this relationship was described, multivariate linear regression analyses were used to evaluate the predictive capacity of functional connectivity in conjunction with other neuroanatomical and behavioral variables described in the literature. Finally, the multivariate linear regression analysis determined the importance of anatomical and functional variables in the prediction of alcohol consumption but failed to find associations with impulsivity, sensation seeking, and executive function scales. In conclusion, the predictive traits obtained in these models were closely associated with changes occurring during adolescence, suggesting the existence of different paths in neurodevelopment that have the potential to influence adolescents' relationship with alcohol consumption.

Wireless optically pumped magnetometer MEG

The current magnetoencephalography (MEG) systems, which rely on cables for control and signal transmission, do not fully realize the potential of wearable optically pumped magnetometers (OPM). This study presents a significant advancement in wireless OPM-MEG by reducing magnetization in the electronics and developing a tailored wireless communication protocol. Our protocol effectively eliminates electromagnetic interference, particularly in the critical frequency bands of MEG signals, and accurately synchronizes the acquisition and stimulation channels with the host computer's clock. We have successfully achieved single-channel wireless OPM-MEG measurement and demonstrated its reliability by replicating three well-established experiments: The alpha rhythm, auditory evoked field, and steady-state visual evoked field in the human brain. Our prototype wireless OPM-MEG system not only streamlines the measurement process but also represents a major step forward in the development of wearable OPM-MEG applications in both neuroscience and clinical research.

Towards non-invasive imaging through spinal-cord generated magnetic fields

Non-invasive imaging of the human spinal cord is a vital tool for understanding the mechanisms underlying its functions in both healthy and pathological conditions. However, non-invasive imaging presents a significant methodological challenge because the spinal cord is difficult to access with conventional neurophysiological approaches, due to its proximity to other organs and muscles, as well as the physiological movements caused by respiration, heartbeats, and cerebrospinal fluid (CSF) flow. Here, we discuss the present state and future directions of spinal cord imaging, with a focus on the estimation of current flow through magnetic field measurements. We discuss existing cryogenic (superconducting) and non-cryogenic (optically-pumped magnetometer-based, OPM) systems, and highlight their strengths and limitations for studying human spinal cord function. While significant challenges remain, particularly in source imaging and interference rejection, magnetic field-based neuroimaging offers a novel avenue for advancing research in various areas. These include sensorimotor processing, cortico-spinal interplay, brain and spinal cord plasticity during learning and recovery from injury, and pain perception. Additionally, this technology holds promise for diagnosing and optimizing the treatment of spinal cord disorders.

DERCo: A Dataset for Human Behaviour in Reading Comprehension Using EEG

This paper introduces the DERCo (Dublin EEG-based Reading Experiment Corpus), a language resource combining electroencephalography (EEG) and next-word prediction data obtained from participants reading narrative texts. The dataset comprises behavioral data collected from 500 participants recruited through the Amazon Mechanical Turk online crowd-sourcing platform, along with EEG recordings from 22 healthy adult native English speakers. The online experiment was designed to examine the context-based word prediction by a large sample of participants, while the EEG-based experiment was developed to extend the validation of behavioral next-word predictability. Online participants were instructed to predict upcoming words and complete entire stories. Cloze probabilities were then calculated for each word so that this predictability measure could be used to support various analyses pertaining to semantic context effects in the EEG recordings. EEG-based analyses revealed significant differences between high and low predictable words, demonstrating one important type of potential analysis that necessitates close integration of these two datasets. This material is a valuable resource for researchers in neurolinguistics due to the word-level EEG recordings in context.

The development of aperiodic and periodic resting-state power between early childhood and adulthood: New insights from optically pumped magnetometers

Neurophysiological signals, comprised of both periodic (e.g., oscillatory) and aperiodic (e.g., non-oscillatory) activity, undergo complex developmental changes between childhood and adulthood. With much of the existing literature primarily focused on the periodic features of brain function, our understanding of aperiodic signals is still in its infancy. Here, we are the first to examine age-related changes in periodic (peak frequency and power) and aperiodic (slope and offset) activity using optically pumped magnetometers (OPMs), a new, wearable magnetoencephalography (MEG) technology that is particularly well-suited for studying development. We examined age-related changes in these spectral features in a sample (N=65) of toddlers (1-3 years), children (4-5 years), young adults (20-26 years), and adults (27-38 years). Consistent with the extant literature, we found significant age-related decreases in the aperiodic slope and offset, and changes in peak frequency and power that were frequency-specific; we are the first to show that the effect sizes of these changes also varied across brain regions. This work not only adds to the growing body of work highlighting the advantages of using OPMs, especially for studying development, but also contributes novel information regarding the variation of neurophysiological changes with age across the brain.

Paediatric magnetoencephalography and its role in neurodevelopmental disorders

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that assesses neurophysiology through the detection of the magnetic fields generated by neural currents. In this way, it is sensitive to brain activity, both in individual regions and brain-wide networks. Conventional MEG systems employ an array of sensors that must be cryogenically cooled to low temperature, in a rigid one-size-fits-all helmet. Systems are typically designed to fit adults and are therefore challenging to use for paediatric measurements. Despite this, MEG has been employed successfully in research to investigate neurodevelopmental disorders, and clinically for presurgical planning for paediatric epilepsy. Here, we review the applications of MEG in children, specifically focussing on autism spectrum disorder and attention-deficit hyperactivity disorder. Our review demonstrates the significance of MEG in furthering our understanding of these neurodevelopmental disorders, while also highlighting the limitations of current instrumentation. We also consider the future of paediatric MEG, with a focus on newly developed instrumentation based on optically pumped magnetometers (OPM-MEG). We provide a brief overview of the development of OPM-MEG systems, and how this new technology might enable investigation of brain function in very young children and infants.

Maternal Nutrition during Pregnancy and Offspring Brain Development: Insights from Neuroimaging

Maternal nutrition during pregnancy is known to be important for offspring growth and health and has also been increasingly recognized for shaping offspring brain development. On the other hand, recent advancements in brain imaging technology have provided unprecedented insights into fetal, neonatal, and pediatric brain morphometry and function. This review synthesizes the current literature regarding the impact of maternal nutrition on offspring brain development, with a specific focus on findings from neuroimaging studies. The diverse effects of maternal nutrients intake or status during pregnancy on neurodevelopmental outcomes in children are discussed. Neuroimaging evidence showed associations between maternal nutrition such as food categories, macronutrients, and micronutrients including vitamins and minerals during pregnancy and child brain imaging features measured using imaging techniques such as ultrasound, magnetic resonance imaging (MRI), electroencephalography (EEG), and magnetoencephalography (MEG). This review demonstrates the capability of neuroimaging in characterizing how maternal nutrition during pregnancy impacts structure and function of the developing brain that may further influence long-term neuropsychological, cognitive, and behavioral outcomes in children. It aims to inspire future research utilizing neuroimaging to deepen our understanding of the critical impacts of maternal nutrition during pregnancy on offspring brain development.

Brain-computer Interaction in the Smart Era

The brain-computer interface (BCI) system serves as a critical link between external output devices and the human brain. A monitored object's mental state, sensory cognition, and even higher cognition are reflected in its electroencephalography (EEG) signal. Nevertheless, unprocessed EEG signals are frequently contaminated with a variety of artifacts, rendering the analysis and elimination of impurities from the collected EEG data exceedingly challenging, not to mention the manual adjustment thereof. Over the last few decades, the rapid advancement of artificial intelligence (AI) technology has contributed to the development of BCI technology. Algorithms derived from AI and machine learning have significantly enhanced the ability to analyze and process EEG electrical signals, thereby expanding the range of potential interactions between the human brain and computers. As a result, the present BCI technology with the help of AI can assist physicians in gaining a more comprehensive understanding of their patients' physical and psychological status, thereby contributing to improvements in their health and quality of life.

Examining predictive coding accounts of typical and autistic neurocognitive development

Predictive coding has emerged as a prominent theoretical framework for understanding perception and its neural underpinnings. There has been a recent surge of interest in the predictive coding framework across the mind sciences. However, comparatively little of the research in this field has investigated the neural underpinnings of predictive coding in young neurotypical and autistic children. This paper provides an overview of predictive coding accounts of typical and autistic neurocognitive development and includes a review of the current electrophysiological evidence supporting these accounts. Based on the current evidence, it is clear that more research in pediatrics is needed to evaluate predictive coding accounts of neurocognitive development fully. If supported, these accounts could have wide-ranging practical implications for pedagogy, parenting, artificial intelligence, and clinical approaches to helping autistic children manage the barrage of everyday sensory information.

A Systematic Review of Aphantasia: Concept, Measurement, Neural Basis, and Theory Development

People with aphantasia exhibit the inability to voluntarily generate or form mental imagery in their minds. Since the term "aphantasia" was proposed to describe this, it has gained increasing attention from psychiatrists, neuroscientists, and clinicians. Previous studies have mainly focused on the definition, prevalence, and measurement of aphantasia, its impacts on individuals' cognitive and emotional processing, and theoretical frameworks synthesizing existing findings, which have contributed greatly to our understanding of aphantasia. However, there are still some debates regarding the conclusions derived from existing research and the theories that were constructed from various sources of evidence. Building upon existing endeavors, this systematic review emphasizes that future research is much needed to refine the definition and diagnosis of aphantasia, strengthen empirical investigations at behavioral and neural levels, and, more importantly, develop or update theories. These multiple lines of efforts could lead to a deeper understanding of aphantasia and further guide researchers in future research directions.

Superconducting Self-Shielded and Zero-Boil-Off Magnetoencephalogram Systems: A Dry Phantom Evaluation

Magnetoencephalography (MEG) systems are advanced neuroimaging tools used to measure the magnetic fields produced by neuronal activity in the human brain. However, they require significant amounts of liquid helium to keep the superconducting quantum interference device (SQUID) sensors in a stable superconducting state. Additionally, MEG systems must be installed in a magnetically shielded room to minimize interference from external magnetic fields. We have developed an advanced MEG system that incorporates a superconducting magnetic shield and a zero-boil-off system. This system overcomes the typical limitations of traditional MEG systems, such as the frequent need for liquid helium refills and the spatial constraints imposed by magnetically shielded rooms. To validate the system, we conducted an evaluation using signal source estimation. This involved a phantom with 50 current sources of known location and magnitude under active zero-boil-off conditions. Our evaluations focused on the precision of the magnetic field distribution and the quantification of estimation errors. We achieved a consistent magnetic field distribution that matched the source current, maintaining an estimation error margin within 3.5 mm, regardless of the frequency of the signal source current. These findings affirm the practicality and efficacy of the system.

The paradoxical brain: paradoxes impact conflict perspectives through increased neural alignment

Mental perspectives can sometimes be changed by psychological interventions. For instance, when applied in the context of intergroup conflicts, interventions, such as the paradoxical thinking intervention, may unfreeze ingrained negative outgroup attitudes and thereby promote progress toward peacemaking. Yet, at present, the evaluation of interventions' impact relies almost exclusively on self-reported and behavioral measures that are informative, but are also prone to social desirability and self-presentational biases. In the present study, magnetoencephalography tracked neural alignment, before and after the paradoxical thinking intervention, during the processing of auditory narratives over the Israeli-Palestinian conflict and thereby evaluated the intervention's potential to change individuals' (n = 80) mental perspectives over the conflict. Compared to baseline, the conflict-targeted intervention yielded a specific significant increased neural alignment in the posterior superior temporal sulcus while processing incongruent as well as congruent political narratives of the conflict. This may be interpreted as a possible change in perspective over the conflict. The results and their interpretations are discussed in view of the critical added value of neuroimaging when assessing interventions to potentially reveal changes in mental perspectives or the way in which they are processed, even in contexts of entrenched resistance to reconsider one's ideological stance.

A novel, robust, and portable platform for magnetoencephalography using optically-pumped magnetometers

Magnetoencephalography (MEG) measures brain function via assessment of magnetic fields generated by neural currents. Conventional MEG uses superconducting sensors, which place significant limitations on performance, practicality, and deployment; however, the field has been revolutionised in recent years by the introduction of optically-pumped magnetometers (OPMs). OPMs enable measurement of the MEG signal without cryogenics, and consequently the conception of "OPM-MEG" systems which ostensibly allow increased sensitivity and resolution, lifespan compliance, free subject movement, and lower cost. However, OPM-MEG is in its infancy with existing limitations on both sensor and system design. Here, we report a new OPM-MEG design with miniaturised and integrated electronic control, a high level of portability, and improved sensor dynamic range. We show that this system produces equivalent measures compared with an established OPM-MEG instrument; specifically, when measuring task-induced beta-band, gamma-band, and evoked neuro-electrical responses, source localisations from the two systems were comparable and temporal correlation of measured brain responses was >0.7 at the individual level and >0.9 for groups. Using an electromagnetic phantom, we demonstrate improved dynamic range by running the system in background fields up to 8 nT. We show that the system is effective in gathering data during free movement (including a sitting-to-standing paradigm) and that it is compatible with simultaneous electroencephalography (EEG). Finally, we demonstrate portability by moving the system between two laboratories. Overall, our new system is shown to be a significant step forward for OPM-MEG and offers an attractive platform for next generation functional medical imaging.

Neurochemical organization of cortical proteinopathy and neurophysiology along the Alzheimer's disease continuum

INTRODUCTION

Despite parallel research indicating amyloid-β accumulation, alterations in cortical neurophysiological signaling, and multi-system neurotransmitter disruptions in Alzheimer's disease (AD), the relationships between these phenomena remains unclear.

METHODS

Using magnetoencephalography, positron emission tomography, and an atlas of 19 neurotransmitters, we studied the alignment between neurophysiological alterations, amyloid-β deposition, and the neurochemical gradients of the cortex.

RESULTS

In patients with mild cognitive impairment and AD, changes in cortical rhythms were topographically aligned with cholinergic, serotonergic, and dopaminergic systems. These alignments correlated with the severity of clinical impairments. Additionally, cortical amyloid-β plaques were preferentially deposited along neurochemical boundaries, influencing how neurophysiological alterations align with muscarinic acetylcholine receptors. Most of the amyloid-β-neurochemical and alpha-band neuro-physio-chemical alignments replicated in an independent dataset of individuals with asymptomatic amyloid-β accumulation.

DISCUSSION

Our findings demonstrate that AD pathology aligns topographically with the cortical distribution of chemical neuromodulator systems and scales with clinical severity, with implications for potential pharmacotherapeutic pathways.

HIGHLIGHTS

Changes in cortical rhythms in Alzheimer's are organized along neurochemical boundaries. The strength of these alignments is related to clinical symptom severity. Deposition of amyloid-β (Aβ) is aligned with similar neurotransmitter systems. Aβ deposition mediates the alignment of beta rhythms with cholinergic systems. Most alignments replicate in participants with pre-clinical Alzheimer's pathology.

Aberrant high-beta band functional connectivity during reward processing in melancholic major depressive disorder: An MEG study

OBJECTIVE

To identify the spatial-temporal pattern variation of whole-brain functional connectivity (FC) during reward processing in melancholic major depressive disorder (MDD) patients, and to determine the clinical correlates of connectomic differences.

METHODS

61 MDD patients and 32 healthy controls were enrolled into the study. During magnetoencephalography (MEG) scanning, all participants completed the facial emotion recognition task. The MDD patients were further divided into two groups: melancholic (n = 31) and non-melancholic (n = 30), based on the Mini International Neuropsychiatric Interview (M.I.N.I.) assessment. Melancholic symptoms were examined by using the 6-item melancholia subscale from the Hamilton Depression Rating Scale (HAM-D6). The whole-brain orthogonalized power envelope connections in the high-beta band (20-35 Hz) were constructed in each period after the happy emotional stimuli (0-200 ms, 100-300 ms, 200-400 ms, 300-500 ms, and 400-600 ms). Then, the network-based statistic (NBS) was used to determine the specific abnormal connection patterns in melancholic MDD patients.

RESULTS

The NBS identified a sub-network difference at the mid-late period (300-500 ms) in response to happy faces among the three groups (corrected P = 0.035). Then, the post hoc and correlation analyses found five FCs were decreased in melancholic MDD patients and were related to HAM-D6 score, including FCs of left fusiform gyrus-right orbital inferior frontal gyrus (r = -0.52, P < 0.001), left fusiform gyrus-left amygdala (r = -0.26, P = 0.049), left posterior cingulate gyrus-right precuneus (r = -0.32, P = 0.025), left precuneus-right precuneus (r = -0.27, P = 0.049), and left precuneus-left inferior occipital gyrus (r = -0.32, P = 0.025).

CONCLUSION

In response to happy faces, melancholic MDD patients demonstrated a disrupted functional connective pattern (20-35 Hz, 300-500 ms), which involved brain regions in visual information processing and the limbic system. The aberrant functional connective pattern in reward processing might be a biomarker of melancholic MDD.

A survey on integral equations for bioelectric modeling

Bioelectric modeling problems, such as electroencephalography, magnetoencephalography, transcranial electrical stimulation, deep brain stimulation, and transcranial magnetic stimulation, among others, can be approached through the formulation and resolution of integral equations of theboundary element method(BEM). Recently, it has been realized that thecharge-based formulationof the BEM is naturally well-suited for the application of thefast multipole method(FMM). The FMM is a powerful algorithm for the computation of many-body interactions and is widely applied in electromagnetic modeling problems. With the introduction of BEM-FMM in the context of bioelectromagnetism, the BEM can now compete with thefinite element method(FEM) in a number of application cases. This survey has two goals: first, to give a modern account of the main BEM formulations in the literature and their integration with FMM, directed to general researchers involved in development of BEM software for bioelectromagnetic applications. Second, to survey different techniques and available software, and to contrast different BEM and FEM approaches. As a new contribution, we showcase that the charge-based formulation is dual to the more common surface potential formulation.

The neuromechanical of Beta-band corticomuscular coupling within the human motor system

Beta-band activity in the sensorimotor cortex is considered a potential biomarker for evaluating motor functions. The intricate connection between the brain and muscle (corticomuscular coherence), especially in beta band, was found to be modulated by multiple motor demands. This coherence also showed abnormality in motion-related disorders. However, although there has been a substantial accumulation of experimental evidence, the neural mechanisms underlie corticomuscular coupling in beta band are not yet fully clear, and some are still a matter of controversy. In this review, we summarized the findings on the impact of Beta-band corticomuscular coherence to multiple conditions (sports, exercise training, injury recovery, human functional restoration, neurodegenerative diseases, age-related changes, cognitive functions, pain and fatigue, and clinical applications), and pointed out several future directions for the scientific questions currently unsolved. In conclusion, an in-depth study of Beta-band corticomuscular coupling not only elucidates the neural mechanisms of motor control but also offers new insights and methodologies for the diagnosis and treatment of motor rehabilitation and related disorders. Understanding these mechanisms can lead to personalized neuromodulation strategies and real-time neurofeedback systems, optimizing interventions based on individual neurophysiological profiles. This personalized approach has the potential to significantly improve therapeutic outcomes and athletic performance by addressing the unique needs of each individual.

Loneliness and brain rhythmic activity in resting state: an exploratory report

Recent studies using resting-state functional magnetic resonance imaging have shown that loneliness is associated with altered blood oxygenation in several brain regions. However, the relationship between loneliness and changes in neuronal rhythm activity in the brain remains unclear. To evaluate brain rhythm, we conducted an exploratory resting-state electroencephalogram (EEG) study of loneliness. We recorded resting-state EEG signals from 139 participants (94 women; mean age = 19.96 years) and analyzed power spectrum density (PSD) and functional connectivity (FC) in both the electrode and source spaces. The PSD analysis revealed significant correlations between loneliness scores and decreased beta-band powers, which may indicate negative emotion, attention, reward, and/or sensorimotor processing. The FC analysis revealed a trend of alpha-band FC associated with individuals' loneliness scores. These findings provide new insights into the neural basis of loneliness, which will facilitate the development of neurobiologically informed interventions for loneliness.

Brain network topological changes in inflammatory bowel disease: an exploratory study

Although the aetio-pathogenesis of inflammatory bowel diseases (IBD) is not entirely clear, the interaction between genetic and adverse environmental factors may induce an intestinal dysbiosis, resulting in chronic inflammation having effects on the large-scale brain network. Here, we hypothesized inflammation-related changes in brain topology of IBD patients, regardless of the clinical form [ulcerative colitis (UC) or Crohn's disease (CD)]. To test this hypothesis, we analysed source-reconstructed magnetoencephalography (MEG) signals in 25 IBD patients (15 males, 10 females; mean age ± SD, 42.28 ± 13.15; mean education ± SD, 14.36 ± 3.58) and 28 healthy controls (HC) (16 males, 12 females; mean age ± SD, 45.18 ± 12.26; mean education ± SD, 16.25 ± 2.59), evaluating the brain topology. The betweenness centrality (BC) of the left hippocampus was higher in patients as compared with controls, in the gamma frequency band. It indicates how much a brain region is involved in the flow of information through the brain network. Furthermore, the comparison among UC, CD and HC showed statistically significant differences between UC and HC and between CD and HC, but not between the two clinical forms. Our results demonstrated that these topological changes were not dependent on the specific clinical form, but due to the inflammatory process itself. Broader future studies involving panels of inflammatory factors and metabolomic analyses on biological samples could help to monitor the brain involvement in IBD and to clarify the clinical impact.

Spatiotemporal responses to emotional conflict and its psychiatric correlates in adolescents with epilepsy using magnetoencephalography

People with epilepsy often suffer from comorbid psychiatric disorders, which negatively affects their quality of life. Emotion regulation is an important cognitive process that is impaired in individuals with psychiatric disorders, such as depression. Adults with epilepsy also show difficulties in emotion regulation, particularly during later-stage, higher-order cognitive processing. Yet, the spatiotemporal and frequency correlates of these functional brain deficits in epilepsy remain unknown, as do the nature of these deficits in adolescent epilepsy. Here, we aim to elucidate the spatiotemporal profile of emotional conflict processing in adolescents with epilepsy, relative to controls, using magnetoencephalography (MEG) and relate these findings to anxiety and depression symptom severity assessed with self-report scales. We hypothesized to see blunted brain activity during emotional conflict in adolescents with epilepsy, relative to controls, in the posterior parietal, prefrontal and cingulate cortices due to their role in explicit and implicit regulation around participant response (500-1000 ms). We analyzed MEG recordings from 53 adolescents (28 epilepsy [14focal,14generalized], 25 controls) during an emotional conflict task. We showed that while controls exhibited behavioral interference to emotional conflict, adolescents with epilepsy failed to exhibit this normative response time pattern. Adolescents with epilepsy showed blunted brain responses to emotional conflict in brain regions related to error evaluation and learning around the average response time (500-700 ms), and in regions involved in decision making during post-response monitoring (800-1000 ms). Interestingly, behavioral patterns and psychiatric symptom severity varied between epilepsy subgroups, wherein those with focal epilepsy showed preserved response time interference. Thus, brain responses were regressed with depression and anxiety levels for each epilepsy subgroup separately. Analyses revealed that under activation in error evaluation regions (500-600 ms) predicted anxiety and depression in focal epilepsy, while regions related to learning (600-700 ms) predicted anxiety in generalized epilepsy, suggesting differential mechanisms of dysfunction in these subgroups. Despite similar rates of anxiety and depression across the groups, adolescents with epilepsy still exhibited deficits in emotional conflict processing in brain and behavioral responses. This suggests that these deficits may exist independently from psychopathology and may stem from underlying dysfunctions that predispose these individuals to develop both disorders. Findings such as these may provide potential targets for future research and therapies.

Neural Basis of Categorical Representations of Animal Body Silhouettes

Neural activities differentiating bodies versus non-body stimuli have been identified in the occipitotemporal cortex of both humans and nonhuman primates. However, the neural mechanisms of coding the similarity of different individuals' bodies of the same species to support their categorical representations remain unclear. Using electroencephalography (EEG) and magnetoencephalography (MEG), we investigated the temporal and spatial characteristics of neural processes shared by different individual body silhouettes of the same species by quantifying the repetition suppression of neural responses to human and animal (chimpanzee, dog, and bird) body silhouettes showing different postures. Our EEG results revealed significant repetition suppression of the amplitudes of early frontal/central activity at 180-220 ms (P2) and late occipitoparietal activity at 220-320 ms (P270) in response to animal (but not human) body silhouettes of the same species. Our MEG results further localized the repetition suppression effect related to animal body silhouettes in the left supramarginal gyrus and left frontal cortex at 200-440 ms after stimulus onset. Our findings suggest two neural processes that are involved in spontaneous categorical representations of animal body silhouettes as a cognitive basis of human-animal interactions.

Modulation of alpha oscillations by attention is predicted by hemispheric asymmetry of subcortical regions

Evidence suggests that subcortical structures play a role in high-level cognitive functions such as the allocation of spatial attention. While there is abundant evidence in humans for posterior alpha band oscillations being modulated by spatial attention, little is known about how subcortical regions contribute to these oscillatory modulations, particularly under varying conditions of cognitive challenge. In this study, we combined MEG and structural MRI data to investigate the role of subcortical structures in controlling the allocation of attentional resources by employing a cued spatial attention paradigm with varying levels of perceptual load. We asked whether hemispheric lateralization of volumetric measures of the thalamus and basal ganglia predicted the hemispheric modulation of alpha-band power. Lateral asymmetry of the globus pallidus, caudate nucleus, and thalamus predicted attention-related modulations of posterior alpha oscillations. When the perceptual load was applied to the target and the distractor was salient caudate nucleus asymmetry predicted alpha-band modulations. Globus pallidus was predictive of alpha-band modulations when either the target had a high load, or the distractor was salient, but not both. Finally, the asymmetry of the thalamus predicted alpha band modulation when neither component of the task was perceptually demanding. In addition to delivering new insight into the subcortical circuity controlling alpha oscillations with spatial attention, our finding might also have clinical applications. We provide a framework that could be followed for detecting how structural changes in subcortical regions that are associated with neurological disorders can be reflected in the modulation of oscillatory brain activity.

The neurophysiological brain-fingerprint of Parkinson's disease

BACKGROUND

Research in healthy young adults shows that characteristic patterns of brain activity define individual "brain-fingerprints" that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson's disease (PD).

METHODS

We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s.

FINDINGS

The arrhythmic spectral components of cortical activity in patients with Parkinson's disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson's brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson's symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology.

INTERPRETATION

The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson's disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets.

FUNDING

Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).

Further characterisation of late somatosensory evoked potentials using electroencephalogram and magnetoencephalogram source imaging

Beside the well-documented involvement of secondary somatosensory area, the cortical network underlying late somatosensory evoked potentials (P60/N60 and P100/N100) is still unknown. Electroencephalogram and magnetoencephalogram source imaging were performed to further investigate the origin of the brain cortical areas involved in late somatosensory evoked potentials, using sensory inputs of different strengths and by testing the correlation between cortical sources. Simultaneous high-density electroencephalograms and magnetoencephalograms were performed in 19 participants, and electrical stimulation was applied to the median nerve (wrist level) at intensity between 1.5 and 9 times the perceptual threshold. Source imaging was undertaken to map the stimulus-induced brain cortical activity according to each individual brain magnetic resonance imaging, during three windows of analysis covering early and late somatosensory evoked potentials. Results for P60/N60 and P100/N100 were compared with those for P20/N20 (early response). According to literature, maximal activity during P20/N20 was found in central sulcus contralateral to stimulation site. During P60/N60 and P100/N100, activity was observed in contralateral primary sensorimotor area, secondary somatosensory area (on both hemispheres) and premotor and multisensory associative cortices. Late responses exhibited similar characteristics but different from P20/N20, and no significant correlation was found between early and late generated activities. Specific clusters of cortical activities were activated with specific input/output relationships underlying early and late somatosensory evoked potentials. Cortical networks, partly common to and distinct from early somatosensory responses, contribute to late responses, all participating in the complex somatosensory brain processing.

Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition

OBJECTIVE

Brain function is understood to be regulated by complex spatiotemporal dynamics, and can be characterized by a combination of observed brain response patterns in time and space. Magnetoencephalography (MEG), with its high temporal resolution, and functional magnetic resonance imaging (fMRI), with its high spatial resolution, are complementary imaging techniques with great potential to reveal information about spatiotemporal brain dynamics. Hence, the complementary nature of these imaging techniques holds much promise to study brain function in time and space, especially when the two data types are allowed to fully interact.

METHODS

We employed coupled tensor/matrix factorization (CMTF) to extract joint latent components in the form of unique spatiotemporal brain patterns that can be used to study brain development and function on a millisecond scale.

RESULTS

Using the CMTF model, we extracted distinct brain patterns that revealed fine-grained spatiotemporal brain dynamics and typical sensory processing pathways informative of high-level cognitive functions in healthy adolescents. The components extracted from multimodal tensor fusion possessed better discriminative ability between high- and low-performance subjects than single-modality data-driven models.

CONCLUSION

Multimodal tensor fusion successfully identified spatiotemporal brain dynamics of brain function and produced unique components with high discriminatory power.

SIGNIFICANCE

The CMTF model is a promising tool for high-order, multimodal data fusion that exploits the functional resolution of MEG and fMRI, and provides a comprehensive picture of the developing brain in time and space.

Non-invasive measurement of rat auditory evoked fields using an optically pumped atomic magnetometer: Effects of task manipulation

Optically pumped magnetometers (OPMs) have become a favorable tool for magnetoencephalography (MEG) measurement, offering a non-invasive method of measurement. OPMs do not require cryogenic environments, sensors can be more closely aligned with the brain. We employed a passive single-stimulus paradigm in conjunction with OPMs with a sensitivity of 20 fT/Hz to investigate the auditory response of rats to inter-stimulus interval (ISI) and frequencies, recording the rat auditory event-related magnetic fields (ERMFs). Our findings include: (1) Auditory evoked fields can be detected non-invasively by OPMs; (2) The amplitude of the rat auditory ERMFs varies with changes in ISI, with more pronounced amplitude changes observed after 5 s; (3) When the sound stimulus frequency is altered at the same ISI, the amplitude of the rats ERMFs changes with frequency, indicating significant differences in attention. Our method offers a valuable tool for the clinical application of a single stimulus paradigm and opens up a new avenue for research on the brain magnetic field detections.

NIR-II Fluorescence Imaging for In Vivo Quantitative Analysis

In vivo real-time qualitative and quantitative analysis is essential for the diagnosis and treatment of diseases such as tumors. Near-infrared-II (NIR-II, 1000-1700 nm) bioimaging is an emerging visualization modality based on fluorescent materials. The advantages of NIR-II region fluorescent materials in terms of reduced photon scattering and low tissue autofluorescence enable NIR-II bioimaging with high resolution and increasing depth of tissue penetration, and thus have great potential for in vivo qualitative and quantitative analysis. In this review, we first summarize recent advances in NIR-II imaging, including fluorescent probe selection, quantitative analysis strategies, and imaging. Then, we describe in detail representative applications to illustrate how NIR-II fluorescence imaging has become an important tool for in vivo quantitative analysis. Finally, we describe the future possibilities and challenges of NIR-II fluorescence imaging.

Binocularly suppressed stimuli induce brain activities related to aesthetic emotions

Introduction

Aesthetic emotions are a class of emotions aroused by evaluating aesthetically appealing objects or events. While evolutionary aesthetics suggests the adaptive roles of these emotions, empirical assessments are lacking. Previous neuroscientific studies have demonstrated that visual stimuli carrying evolutionarily important information induce neural responses even when presented non-consciously. To examine the evolutionary importance of aesthetic emotions, we conducted a neuroscientific study using magnetoencephalography (MEG) to measure induced neural responses to non-consciously presented portrait paintings categorised as biological and non-biological and examined associations between the induced responses and aesthetic ratings.

Methods

MEG and pre-rating data were collected from 23 participants. The pre-rating included visual analogue scales for object saliency, facial saliency, liking, and beauty scores, in addition to 'biologi-ness,' which was used for subcategorising stimuli into biological and non-biological. The stimuli were presented non-consciously using a continuous flash suppression paradigm or consciously using binocular presentation without flashing masks, while dichotomic behavioural responses were obtained (beauty or non-beauty). Time-frequency decomposed MEG data were used for correlation analysis with pre-rating scores for each category.

Results

Behavioural data revealed that saliency scores of non-consciously presented stimuli influenced dichotomic responses (beauty or non-beauty). MEG data showed that non-consciously presented portrait paintings induced spatiotemporally distributed low-frequency brain activities associated with aesthetic ratings, which were distinct between the biological and non-biological categories and conscious and non-conscious conditions.

Conclusion

Aesthetic emotion holds evolutionary significance for humans. Neural pathways are sensitive to visual images that arouse aesthetic emotion in distinct ways for biological and non-biological categories, which are further influenced by consciousness. These differences likely reflect the diversity in mechanisms of aesthetic processing, such as processing fluency, active elaboration, and predictive processing. The aesthetic processing of non-conscious stimuli appears to be characterised by fluency-driven affective processing, while top-down regulatory processes are suppressed. This study provides the first empirical evidence supporting the evolutionary significance of aesthetic processing.

Infant neuroscience: how to measure brain activity in the youngest minds

The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.

From bench to bedside: Overview of magnetoencephalography in basic principle, signal processing, source localization and clinical applications

Magnetoencephalography (MEG) is a non-invasive technique that can precisely capture the dynamic spatiotemporal patterns of the brain by measuring the magnetic fields arising from neuronal activity along the order of milliseconds. Observations of brain dynamics have been used in cognitive neuroscience, the diagnosis of neurological diseases, and the brain-computer interface (BCI). In this study, we outline the basic principle, signal processing, and source localization of MEG, and describe its clinical applications for cognitive assessment, the diagnoses of neurological diseases and mental disorders, preoperative evaluation, and the BCI. This review not only provides an overall perspective of MEG, ranging from practical techniques to clinical applications, but also enhances the prevalent understanding of neural mechanisms. The use of MEG is expected to lead to significant breakthroughs in neuroscience.

Alignments between cortical neurochemical systems, proteinopathy and neurophysiological alterations along the Alzheimer's disease continuum

Two neuropathological hallmarks of Alzheimer's disease (AD) are the accumulation of amyloid-β (Aβ) proteins and alterations in cortical neurophysiological signaling. Despite parallel research indicating disruption of multiple neurotransmitter systems in AD, it has been unclear whether these two phenomena are related to the neurochemical organization of the cortex. We leveraged task-free magnetoencephalography and positron emission tomography, with a cortical atlas of 19 neurotransmitters to study the alignment and interactions between alterations of neurophysiological signaling, Aβ deposition, and the neurochemical gradients of the human cortex. In patients with amnestic mild cognitive impairment (N = 18) and probable AD (N = 20), we found that changes in rhythmic, but not arrhythmic, cortical neurophysiological signaling relative to healthy controls (N = 20) are topographically aligned with cholinergic, serotonergic, and dopaminergic neurochemical systems. These neuro-physio-chemical alignments are related to the severity of cognitive and behavioral impairments. We also found that cortical Aβ plaques are preferentially deposited along neurochemical boundaries, and mediate how beta-band rhythmic cortical activity maps align with muscarinic acetylcholine receptors. Finally, we show in an independent dataset that many of these alignments manifest in the asymptomatic stages of cortical Aβ accumulation (N = 33; N = 71 healthy controls), particularly the Aβ-neurochemical alignments (57.1%) and neuro-physio-chemical alignments in the alpha frequency band (62.5%). Overall, the present study demonstrates that the expression of pathology in pre-clinical and clinical AD aligns topographically with the cortical distribution of chemical neuromodulator systems, scaling with clinical severity and with implications for potential pharmacotherapeutic pathways.

A bicoherence approach to analyze multi-dimensional cross-frequency coupling in EEG/MEG data

We introduce a blockwise generalisation of the Antisymmetric Cross-Bicoherence (ACB), a statistical method based on bispectral analysis. The Multi-dimensional ACB (MACB) is an approach that aims at detecting quadratic lagged phase-interactions between vector time series in the frequency domain. Such a coupling can be empirically observed in functional neuroimaging data, e.g., in electro/magnetoencephalographic signals. MACB is invariant under orthogonal trasformations of the data, which makes it independent, e.g., on the choice of the physical coordinate system in the neuro-electromagnetic inverse procedure. In extensive synthetic experiments, we prove that MACB performance is significantly better than that obtained by ACB. Specifically, the shorter the data length, or the higher the dimension of the single data space, the larger the difference between the two methods.

Alterations of Cortical Structure and Neurophysiology in Parkinson's Disease Are Aligned with Neurochemical Systems

OBJECTIVE

Parkinson's disease (PD) affects the structural integrity and neurophysiological signaling of the cortex. These alterations are related to the motor and cognitive symptoms of the disease. How these changes are related to the neurochemical systems of the cortex is unknown.

METHODS

We used T1-weighted magnetic resonance imaging (MRI) and magnetoencephalography (MEG) to measure cortical thickness and task-free neurophysiological activity in patients with idiopathic PD (nMEG = 79, nMRI = 65) and matched healthy controls (nMEG = 65, nMRI = 37). Using linear mixed-effects models, we examined the topographical alignment of cortical structural and neurophysiological alterations in PD with cortical atlases of 19 neurotransmitter receptor and transporter densities.

RESULTS

We found that neurophysiological alterations in PD occur primarily in brain regions rich in acetylcholinergic, serotonergic, and glutamatergic systems, with protective implications for cognitive and psychiatric symptoms. In contrast, cortical thinning occurs preferentially in regions rich in noradrenergic systems, and the strength of this alignment relates to motor deficits.

INTERPRETATION

This study shows that the spatial organization of neurophysiological and structural alterations in PD is relevant for nonmotor and motor impairments. The data also advance the identification of the neurochemical systems implicated. The approach uses novel nested atlas modeling methodology that is transferrable to research in other neurological and neuropsychiatric diseases and syndromes. ANN NEUROL 2024;95:802-816.

Neurophysiological brain function predicts response to cognitive rehabilitation and mindfulness in multiple sclerosis: a randomized trial

BACKGROUND

Cognitive treatment response varies highly in people with multiple sclerosis (PwMS). Identification of mechanisms is essential for predicting response.

OBJECTIVES

This study aimed to investigate whether brain network function predicts response to cognitive rehabilitation therapy (CRT) and mindfulness-based cognitive therapy (MBCT).

METHODS

PwMS with cognitive complaints completed CRT, MBCT, or enhanced treatment as usual (ETAU) and performed three measurements (baseline, post-treatment, 6-month follow-up). Baseline magnetoencephalography (MEG) measures were used to predict treatment effects on cognitive complaints, personalized cognitive goals, and information processing speed (IPS) using mixed models (secondary analysis REMIND-MS study).

RESULTS

We included 105 PwMS (96 included in prediction analyses; 32 CRT, 31 MBCT, 33 ETAU), and 56 healthy controls with baseline MEG. MEG did not predict reductions in complaints. Higher connectivity predicted better goal achievement after MBCT (p = 0.010) and CRT (p = 0.018). Lower gamma power (p = 0.006) and higher connectivity (p = 0.020) predicted larger IPS benefits after MBCT. These MEG predictors indicated worse brain function compared to healthy controls (p < 0.05).

CONCLUSIONS

Brain network function predicted better cognitive goal achievement after MBCT and CRT, and IPS improvements after MBCT. PwMS with neuronal slowing and hyperconnectivity were most prone to show treatment response, making network function a promising tool for personalized treatment recommendations.

TRIAL REGISTRATION

The REMIND-MS study was prospectively registered in the Dutch Trial registry (NL6285; https://trialsearch.who.int/Trial2.aspx?TrialID=NTR6459 ).

Multispectral brain connectivity during visual attention distinguishes controlled from uncontrolled hypertension

Hypertension-related changes in brain function place individuals at higher risk for cognitive impairment and Alzheimer's disease. The existing functional neuroimaging literature has identified important neural and behavioural differences between normotensive and hypertensive individuals. However, previously-used methods (i.e. magnetic resonance imaging, functional near-infrared spectroscopy) rely on neurovascular coupling, which is a useful but indirect measure of neuronal activity. Furthermore, most studies fail to distinguish between controlled and uncontrolled hypertensive individuals, who exhibit significant behavioural and clinical differences. To partially remedy this gap in the literature, we used magnetoencephalography (MEG) to directly examine neuronal activity that is invariant to neurovascular coupling changes induced by hypertension. Our study included 52 participants (19 healthy controls, 15 controlled hypertensives, 18 uncontrolled hypertensives) who completed a modified flanker attention task during MEG. We identified significant oscillatory neural responses in two frequencies (alpha: 8-14 Hz, gamma: 48-60 Hz) for imaging and used grand-averaged images to determine seeds for whole-brain connectivity analysis. We then conducted Fisher-z tests for each pair of groups, using the relationship between the neural connectivity and behavioural attention effects. This highlighted a distributed network of regions associated with cognitive control and selective attention, including frontal-occipital and interhemispheric occipital connections. Importantly, the inferior frontal cortex exhibited a unique neurobehavioural relationship that distinguished the uncontrolled hypertensive group from the controlled hypertensive and normotensive groups. This is the first investigation of hypertension using MEG and identifies critical whole-brain connectivity differences based on hypertension profiles. KEY POINTS: Structural and functional changes in brain circuitry scale with hypertension severity and increase the risk of cognitive impairment and Alzheimer's disease. We harness the excellent spatiotemporal precision of magnetoencephalography (MEG) to directly quantify dynamic functional connectivity in healthy control, controlled hypertensive and uncontrolled hypertensive groups during a flanker task. In the first MEG study of hypertension, we show that there are neurobehavioural relationships that distinguish the uncontrolled hypertensive group from healthy and controlled hypertensive group in the prefrontal cortex. These results provide novel insights into the differential impact of hypertension on brain dynamics underlying selective attention.

A Multivariate analysis on evoked components of Chinese semantic congruity: an OP-MEG study with EEG

The application of wearable magnetoencephalography using optically-pumped magnetometers has drawn extensive attention in the field of neuroscience. Electroencephalogram system can cover the whole head and reflect the overall activity of a large number of neurons. The efficacy of optically-pumped magnetometer in detecting event-related components can be validated through electroencephalogram results. Multivariate pattern analysis is capable of tracking the evolution of neurocognitive processes over time. In this paper, we adopted a classical Chinese semantic congruity paradigm and separately collected electroencephalogram and optically-pumped magnetometer signals. Then, we verified the consistency of optically-pumped magnetometer and electroencephalogram in detecting N400 using mutual information index. Multivariate pattern analysis revealed the difference in decoding performance of these two modalities, which can be further validated by dynamic/stable coding analysis on the temporal generalization matrix. The results from searchlight analysis provided a neural basis for this dissimilarity at the magnetoencephalography source level and the electroencephalogram sensor level. This study opens a new avenue for investigating the brain's coding patterns using wearable magnetoencephalography and reveals the differences in sensitivity between the two modalities in reflecting neuron representation patterns.

Is source-resolved magnetoencephalographic mismatch negativity a viable biomarker for early psychosis?

Mismatch negativity (MMN) is an auditory event-related response reflecting the pre-attentive detection of novel stimuli and is a biomarker of cortical dysfunction in schizophrenia (SZ). MMN to pitch (pMMN) and to duration (dMMN) deviant stimuli are impaired in chronic SZ, but it is less clear if MMN is reduced in first-episode SZ, with inconsistent findings in scalp-level EEG studies. Here, we investigated the neural generators of pMMN and dMMN with MEG recordings in 26 first-episode schizophrenia spectrum (FEsz) and 26 matched healthy controls (C). We projected MEG inverse solutions into precise functionally meaningful auditory cortex areas. MEG-derived MMN sources were in bilateral primary auditory cortex (A1) and belt areas. In A1, pMMN FEsz reduction showed a trend towards statistical significance (F(1,50) = 3.31; p = .07), and dMMN was reduced in FEsz (F(1,50) = 4.11; p = .04). Hypothesis-driven comparisons at each hemisphere revealed dMMN reduction in FEsz occurred in the left (t(56) = 2.23; p = .03; d = .61) but not right (t(56) = 1.02; p = .31; d = .28) hemisphere, with a moderate effect size. The added precision of MEG source solution with high-resolution MRI and parcellation of A1 may be requisite to detect the emerging pathophysiology and indicates a critical role for left hemisphere pathology at psychosis onset. However, the moderate effect size in left A1, albeit larger than reported in scalp MMN meta-analyses, casts doubt on the clinical utility of MMN for differential diagnosis, as a majority of patients will overlap with the healthy individual's distribution.

Impaired long-range excitatory time scale predicts abnormal neural oscillations and cognitive deficits in Alzheimer's disease

BACKGROUND

Alzheimer's disease (AD) is the most common form of dementia, progressively impairing cognitive abilities. While neuroimaging studies have revealed functional abnormalities in AD, how these relate to aberrant neuronal circuit mechanisms remains unclear. Using magnetoencephalography imaging we documented abnormal local neural synchrony patterns in patients with AD. To identify global abnormal biophysical mechanisms underlying the spatial and spectral electrophysiological patterns in AD, we estimated the parameters of a biophysical spectral graph model (SGM).

METHODS

SGM is an analytic neural mass model that describes how long-range fiber projections in the brain mediate the excitatory and inhibitory activity of local neuronal subpopulations. Unlike other coupled neuronal mass models, the SGM is linear, available in closed-form, and parameterized by a small set of biophysical interpretable global parameters. This facilitates their rapid and unambiguous inference which we performed here on a well-characterized clinical population of patients with AD (N = 88, age = 62.73 +/- 8.64 years) and a cohort of age-matched controls (N = 88, age = 65.07 +/- 9.92 years).

RESULTS

Patients with AD showed significantly elevated long-range excitatory neuronal time scales, local excitatory neuronal time scales and local inhibitory neural synaptic strength. The long-range excitatory time scale had a larger effect size, compared to local excitatory time scale and inhibitory synaptic strength and contributed highest for the accurate classification of patients with AD from controls. Furthermore, increased long-range time scale was associated with greater deficits in global cognition.

CONCLUSIONS

These results demonstrate that long-range excitatory time scale of neuronal activity, despite being a global measure, is a key determinant in the local spectral signatures and cognition in the human brain, and how it might be a parsimonious factor underlying altered neuronal activity in AD. Our findings provide new insights into mechanistic links between abnormal local spectral signatures and global connectivity measures in AD.

An advance in novel intelligent sensory technologies: From an implicit-tracking perspective of food perception

Food sensory evaluation mainly includes explicit and implicit measurement methods. Implicit measures of consumer perception are gaining significant attention in food sensory and consumer science as they provide effective, subconscious, objective analysis. A wide range of advanced technologies are now available for analyzing physiological and psychological responses, including facial analysis technology, neuroimaging technology, autonomic nervous system technology, and behavioral pattern measurement. However, researchers in the food field often lack systematic knowledge of these multidisciplinary technologies and struggle with interpreting their results. In order to bridge this gap, this review systematically describes the principles and highlights the applications in food sensory and consumer science of facial analysis technologies such as eye tracking, facial electromyography, and automatic facial expression analysis, as well as neuroimaging technologies like electroencephalography, magnetoencephalography, functional magnetic resonance imaging, and functional near-infrared spectroscopy. Furthermore, we critically compare and discuss these advanced implicit techniques in the context of food sensory research and then accordingly propose prospects. Ultimately, we conclude that implicit measures should be complemented by traditional explicit measures to capture responses beyond preference. Facial analysis technologies offer a more objective reflection of sensory perception and attitudes toward food, whereas neuroimaging techniques provide valuable insight into the implicit physiological responses during food consumption. To enhance the interpretability and generalizability of implicit measurement results, further sensory studies are needed. Looking ahead, the combination of different methodological techniques in real-life situations holds promise for consumer sensory science in the field of food research.

The Early Subcortical Response at the Fundamental Frequency of Speech Is Temporally Separated from Later Cortical Contributions

Most parts of speech are voiced, exhibiting a degree of periodicity with a fundamental frequency and many higher harmonics. Some neural populations respond to this temporal fine structure, in particular at the fundamental frequency. This frequency-following response to speech consists of both subcortical and cortical contributions and can be measured through EEG as well as through magnetoencephalography (MEG), although both differ in the aspects of neural activity that they capture: EEG is sensitive to both radial and tangential sources as well as to deep sources, whereas MEG is more restrained to the measurement of tangential and superficial neural activity. EEG responses to continuous speech have shown an early subcortical contribution, at a latency of around 9 msec, in agreement with MEG measurements in response to short speech tokens, whereas MEG responses to continuous speech have not yet revealed such an early component. Here, we analyze MEG responses to long segments of continuous speech. We find an early subcortical response at latencies of 4-11 msec, followed by later right-lateralized cortical activities at delays of 20-58 msec as well as potential subcortical activities. Our results show that the early subcortical component of the FFR to continuous speech can be measured from MEG in populations of participants and that its latency agrees with that measured with EEG. They furthermore show that the early subcortical component is temporally well separated from later cortical contributions, enabling an independent assessment of both components toward further aspects of speech processing.

Interictal magnetic signals in new-onset Rolandic epilepsy may help with timing of treatment selection

OBJECTIVE

With research progress on Rolandic epilepsy (RE), its "benign" nature has been phased out. Clinicians are exhibiting an increasing tendency toward a more assertive treatment approach for RE. Nonetheless, in clinical practice, delayed treatment remains common because of the "self-limiting" nature of RE. Therefore, this study aimed to identify an imaging marker to aid treatment decisions and select a more appropriate time for initiating therapy for RE.

METHODS

We followed up with children newly diagnosed with RE, classified them into medicated and non-medicated groups according to the follow-up results, and compared them with matched healthy controls. Before beginning follow-up visits, interictal magnetic data were collected using magnetoencephalography in treatment-naïve recently diagnosed patients. The spectral power of the whole brain during initial diagnosis was determined using minimum normative estimation combined with the Welch technique.

RESULTS

A difference was observed in the magnetic source intensity within the left caudal anterior cingulate and precentral and postcentral gyri in the delta band between the medicated and non-medicated groups. The results revealed good discriminatory ability within the receiver operator characteristic curve. In the medicated group, there was a specific change in the frontotemporal magnetic source intensity, which shifted from high to low frequencies, compared with the healthy control group.

SIGNIFICANCE

The intensity of the precentral gyrus magnetic source within the delta band showed good specificity. Considering the rigor of initial treatment, the intensity of the precentral gyrus magnetic source can provide some help as an imaging marker for initial RE treatment, particularly for the timing of treatment initiation.

The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study

Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.

Temporal Unfolding of Racial Ingroup Bias in Neural Responses to Perceived Dynamic Pain in Others

In this study, we investigated how empathic neural responses unfold over time in different empathy networks when viewing same-race and other-race individuals in dynamic painful conditions. We recorded magnetoencephalography signals from Chinese adults when viewing video clips showing a dynamic painful (or non-painful) stimulation to Asian and White models' faces to trigger painful (or neutral) expressions. We found that perceived dynamic pain in Asian models modulated neural activities in the visual cortex at 100 ms-200 ms, in the orbitofrontal and subgenual anterior cingulate cortices at 150 ms-200 ms, in the anterior cingulate cortex around 250 ms-350 ms, and in the temporoparietal junction and middle temporal gyrus around 600 ms after video onset. Perceived dynamic pain in White models modulated activities in the visual, anterior cingulate, and primary sensory cortices after 500 ms. Our findings unraveled earlier dynamic activities in multiple neural circuits in response to same-race (vs other-race) individuals in dynamic painful situations.

Limiting parameter range for cortical-spherical mapping improves activated domain estimation for attention modulated auditory response

BACKGROUND

Attention is one of the factors involved in selecting input information for the brain. We applied a method for estimating domains with clear boundaries using magnetoencephalography (the domain estimation method) for auditory-evoked responses (N100m) to evaluate the effects of attention in milliseconds. However, because the surface around the auditory cortex is folded in a complicated manner, it is unknown whether the activity in the auditory cortex can be estimated.

NEW METHOD

The parameter range to express current sources was set to include the auditory cortex. Their search region was expressed as a direct product of the parameter ranges used in the adaptive diagonal curves.

RESULTS

Without a limitation of the range, activity was estimated in regions other than the auditory cortex in all cases. However, with the limitation of the range, the activity was estimated in the primary or higher auditory cortex. Further analysis of the limitation of the range showed that the domains activated during attention included the regions activated during no attention for the participants whose amplitudes of N100m were higher during attention.

COMPARISON WITH EXISTING METHOD

We proposed a method for effectively limiting the search region to evaluate the extent of the activated domain in regions with complex folded structures.

CONCLUSION

To evaluate the extent of activated domains in regions with complex folded structures, it is necessary to limit the parameter search range. The area of the activated domains in the auditory cortex may increase by attention on the millisecond timescale.